Various representational formats have developed over time to organize and to represent information. Specifically, organizational charts, tables, decision trees, and histograms are some of the traditional formats for organizing and reporting data. Once the underlying data is organized into a particular format, it can be used for a desired purpose. However, the utility of these traditional formats are often subject to certain limitations.
Some format specific limitations arise because the representational capacity of a given format is exceeded by the amount of data required to accurately model a system. For example, a table of data cannot represent a large and complex system without becoming voluminous and unwieldy for a human analyst to parse. As a result, tables and other formats sometimes enforce an unrealistic view of the world where only one facet of a larger system is considered in isolation. Accordingly, data representation techniques that encourage analytic approaches that expand perspectives and change outmoded norms are needed. However, other limitations result when dealing with complex systems.
Mismatches between the nature of the data format and the nature of the underlying data can lead to another data format limitation. For example, a table of increasing values may indicate a pattern at first viewing. However, without supplemental calculations, the details of the pattern remain obscured. Thus, some of the traditional representation formats introduced above are inherently limited. As such, they are best suited for simple data and systems.
In contrast, complex systems or relationships with periodic or persistent non-linear components cannot always be easily handled by traditional data representations. Flexible and intuitive approaches to data representation are needed to address these deficiencies.
Currently, data representation and analytic tools based upon conventional teachings are difficult to use. They often include non-intuitive interfaces that make it difficult to extract meaningful information about the larger system. As discussed above, various limitations exist with regard to traditional data representation formats. Consequently, a need therefore exists for techniques and apparatus that are intuitive, adaptable, and suitable for modeling complex systems or individual system components.